Actually, I spoke too soon. (I should have known better -- always test first.) But: >>>import SafeEval as se >>>se.safeEval('[["AAPL", 35.5, 0.45],["YHOO", 75.68, 0.01]]') [['AAPL', 35.5, 0.45000000000000001], ['YHOO', 75.680000000000007, 0.01]] >>>se.safeEval('[["AAPL", 35.5, 0.45],["YHOO", 75.68, -0.01]]') SyntaxError: malformed _expression_ (-) Seems that parsing negative numbers is outside of the scope of this routine. Here's the source (which is Frederik's source with one minor renaming; I take no credit here); anyone have any ideas? B. ==== start source ==== import cStringIO, tokenize def sequence(next, token, end): out = [] token = next() while token[1] != end: out.append(atom(next, token)) token = next() if token[1] == "," or token[1] == ":": token = next() return out def atom(next, token): if token[1] == "(": return tuple(sequence(next, token, ")")) elif token[1] == "[": return sequence(next, token, "]") elif token[1] == "{": seq = sequence(next, token, "}") res = {} for i in range(0, len(seq), 2): res[seq[i]] = seq[i+1] return res elif token[0] in (tokenize.STRING, tokenize.NUMBER): return eval(token[1]) # safe use of eval! raise SyntaxError("malformed _expression_ (%s)" % token[1]) def safeEval(source): src = "" src = "" src = "" for token in src if token[0] is not tokenize.NL) res = atom(src.next, src.next()) if src.next()[0] is not tokenize.ENDMARKER: raise SyntaxError("bogus data after _expression_") return res ==== end source ==== -- Brendon Towle, PhD Cognitive Scientist +1-412-690-2442x127 Carnegie Learning, Inc. The Cognitive Tutor Company ® Helping over 375,000 students in 1000 school districts succeed in math. |
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